5G/B5G异构网络切换过程分析和移动性管理解决方案

有效的移动性管理对于确保5G异构网络预期的QoS和QoE至关重要。切换过程在移动性管理中起着至关重要的作用。在此过程中的故障可能会对5G通信网络的可靠性、稳定性和连接性产生不利影响。对5G HetNet的切换过程进行了分析,包括5G切换过程步骤、5G HetNet的三层切换、5G HetNet的关键切换参数。此外,针对具体问题,如超高速、负载均衡和小区间干扰,归纳总结了5G HetNet的移动性管理主要解决方案,并提出了5G/B5G HetNet的移动性管理新方法。

Channel assignment and power allocation for throughput improvement with PPO in B5G heterogeneous edge networks

In Beyond the Fifth Generation(B5G)heterogeneous edge networks,numerous users are multiplexed on a channel or served on the same frequency resource block,in which case the transmitter applies coding and the receiver uses interference cancellation.Unfortunately,uncoordinated radio resource allocation can reduce system throughput and lead to user inequity,for this reason,in this paper,channel allocation and power allocation problems are formulated to maximize the system sum rate and minimum user achievable rate.Since the construction model is non-convex and the response variables are high-dimensional,a distributed Deep Reinforcement Learning(DRL)framework called distributed Proximal Policy Optimization(PPO)is proposed to allocate or assign resources.Specifically,several simulated agents are trained in a heterogeneous environment to find robust behaviors that perform well in channel assignment and power allocation.Moreover,agents in the collection stage slow down,which hinders the learning of other agents.Therefore,a preemption strategy is further proposed in this paper to optimize the distributed PPO,form DP-PPO and successfully mitigate the straggler problem.The experimental results show that our mechanism named DP-PPO improves the performance over other DRL methods.

QoE oriented intelligent online learning evaluation technology in B5G scenario

Students'demand for online learning has exploded during the post-COvID-19 pandemic era.However,due to their poor learning experience,students'dropout rate and learning performance of online learning are not always satisfactory.The technical advantages of Beyond Fifth Generation(B5G)can guarantee a good multimedia Quality of Experience(QoE).As a special case of multimedia services,online learning takes into account both the usability of the service and the cognitive development of the users.Factors that affect the Quality of Online Learning Experience(OL-QoE)become more complicated.To get over this dilemma,we propose a systematic scheme by integrating big data,Machine Learning(ML)technologies,and educational psychology theory.Specifically,we first formulate a general definition of OL-QoE by data analysis and experimental verification.This formula considers both the subjective and objective factors(i.e.,video watching ratio and test scores)that most affect OLQoE.Then,we induce an extended layer to the classic Broad Learning System(BLS)to construct an Extended Broad Learning System(EBLS)for the students'OL-QoE prediction.Since the extended layer can increase the width of the BLS model and reduce the redundant nodes of BLS,the proposed EBLS can achieve a trade-off between the prediction accuracy and computation complexity.Finally,we provide a series of early intervention suggestions for different types of students according to their predicted OL-QoE values.Through timely interventions,their OL-QoE and learning performance can be improved.Experimental results verify the effectiveness oftheproposed scheme.

Analysis on unit maximum capacity of orthogonal multiple watermarking for multimedia signals in B5G wireless communications

Beyond-5G(B5G)aims to meet the growing demands of mobile traffic and expand the communication space.Considering that intelligent applications to B5G wireless communications will involve security issues regarding user data and operational data,this paper analyzes the maximum capacity of the multi-watermarking method for multimedia signal hiding as a means of alleviating the information security problem of B5G.The multiwatermarking process employs spread transform dither modulation.During the watermarking procedure,Gram-Schmidt orthogonalization is used to obtain the multiple spreading vectors.Consequently,multiple watermarks can be simultaneously embedded into the same position of a multimedia signal.Moreover,the multiple watermarks can be extracted without affecting one another during the extraction process.We analyze the effect of the size of the spreading vector on the unit maximum capacity,and consequently derive the theoretical relationship between the size of the spreading vector and the unit maximum capacity.A number of experiments are conducted to determine the optimal parameter values for maximum robustness on the premise of high capacity and good imperceptibility.

Reinforcement learning based edge computing in B5G

The development of communication technology will promote the application of Internet of Things,and Beyond 5G will become a new technology promoter.At the same time,Beyond 5G will become one of the important supports for the development of edge computing technology.This paper proposes a communication task allocation algorithm based on deep reinforcement learning for vehicle-to-pedestrian communication scenarios in edge computing.Through trial and error learning of agent,the optimal spectrum and power can be determined for transmission without global information,so as to balance the communication between vehicle-to-pedestrian and vehicle-to-infrastructure.The results show that the agent can effectively improve vehicle-to-infrastructure communication rate as well as meeting the delay constraints on the vehicle-to-pedestrian link.

Satellite Communications with 5G, B5G, and 6G: Challenges and Prospects

Satellite communications, pivotal for global connectivity, are increasingly converging with cutting-edge mobile networks, notably 5G, B5G, and 6G. This amalgamation heralds the promise of universal, high-velocity communication, yet it is not without its challenges. Paramount concerns encompass spectrum allocation, the harmonization of network architectures, and inherent latency issues in satellite transmissions. Potential mitigations, such as dynamic spectrum sharing and the deployment of edge computing, are explored as viable solutions. Looking ahead, the advent of quantum communications within satellite frameworks and the integration of AI spotlight promising research trajectories. These advancements aim to foster a seamless and synergistic coexistence between satellite communications and next-gen mobile networks.

B5G车联网关键技术分析

文章介绍5G-V2X(5G车联网)在3GPP标准中的发展情况、性能指标、技术功能、应用场景,并研究分析核心技术Sidelink(侧链通信),描述如车辆编队、高级驾驶等应用场景。文章着重分析未来B5G(后5G)时代车联网可能被广泛运用的多种增强技术如UE(用户设备)增强、定位增强、车载中继和机器学习,最后总结展望未来车联网发展前景。

5G时代智慧图书馆服务功能再造模式研究

随着5G通信技术规模化应用,大数据、云计算、人工智能等信息技术将图书馆带入一个智慧化的时代,给智慧图书馆服务功能带来了重大变革,探索创新符合时代要求的智慧服务模式是图书馆人必然历史责任。文章针对5G技术对智慧图书馆的影响因素,提出了应用现代化信息技术重构用户资源库、知识资源库、智慧馆员培养体系、智慧阅读服务平台和联盟协同服务平台,赋予图书馆智慧服务新功能。5G时代智慧图书馆服务功能再造模式更能满足用户深层次、多样化、精准化、个性化的服务新需求。

5G技术试点建设助力数字贸易国际竞争力提升

5G技术试点建设成为提升数字贸易国际竞争力的重要途径。本文选取2005-2021年CEIC全球经济数据库中的292个地级市作为研究对象,利用多时点DID模型评估5G技术试点建设对数字贸易国际竞争力的影响及作用机制。发现5G技术试点建设能显著提升我国数字贸易国际竞争力;技术创新是5G技术试点建设与数字贸易国际竞争力的中介变量;产业结构合理化和产业结构高级化在5G技术试点建设对数字贸易国际竞争力的影响中存在中介效应;5G技术试点建设政策对我国数字贸易国际竞争力的促进作用在开通中欧班列的城市相对更大;5G技术试点建设对数字贸易国际竞争力的间接效应大于直接效应。因此,应制定财税政策,鼓励企业通过数字化转型实现产业升级,不断提升中欧班列开通对我国数字贸易国际竞争力的促进作用。

5G全息远程互动智慧教室设计与应用

智慧教室是推动现代信息技术与教育教学深度融合的重点研究领域和研究热点。首先分析智慧教室发展现状,指出利用常规智慧教室开展远程教学活动时存在的互动性不足、临场感缺失等问题。然后基于全息投影技术全沉浸性、全数据化、全互动性的特征,以及5G通信技术高带宽、低延时的优势,提出一种融合5G和全息投影技术的新型远程互动智慧教室设计方案,并在方案整体架构、各软硬件子系统设计以及教室结构设计等方面进行详细的阐述。这种5G全息智慧教室应用场景广阔,不仅能够以裸眼3D的效果展示全息三维模型,还可以将授课教师的全息三维影像投影到远程教室中,增强异地远程互动教学中远程听课学生的临场感和沉浸感,提高学生学习的积极性和主动性。

基于5G移动通信技术在医疗设备管理中的研究

目的 为解决现有医疗设备通信技术滞后、设备管理能力欠佳等问题,提出一种基于5G移动通信技术在医疗设备管理中的方法,以提高医疗设备之间的数据信息通信能力。方法 基于5G通信技术,融合安全传输层协议,对传输数据进行加密;结合WebRTC技术,实现远程视频通话和会诊;使用离群检测算法对数据进行处理,提高通信数据的信息检索能力;加入网络波动检测模块,降低在远程访问中网络波动带来的影响。结果 通过记录某医疗机构某年1—10月的远程视频次数及网络波动次数和触发网络加速模块的次数可知,本系统将目标特征误差保持在2%以下,在系统运行过程中非常稳定且适用。结论 本系统大大减轻了系统主机的压力,具有较高的工作效率及较低的误差率和波动率,可达到远程医用和远程急救的要求。

5G高铁专网覆盖综合解决方案研究和应用

5G高铁覆盖面临着资源占时短、瞬时容量高、车体损耗大、移动速度快、基站交替快和远近兼顾难等多重挑战。本文针对5G高铁专网的覆盖方案、容量方案、公专网频率协同方案、主设备与天线选型方案、优化创新方案五大关键点开展了对比论证和深入研究,并应用于某高铁规划建设优化实践中,提升了高铁客户的感知,满足了“5G高铁上车”过渡期的高铁场景5G覆盖需求,为后续高铁覆盖项目的应用推广提供了重要的参考。

基于5G多接入边缘计算的云化PLC系统架构设计与应用

随着工业控制系统对柔性化、扁平化的要求不断提升,以PLC为构建基础的传统工业控制网络在大规模接入、算力提升和部署灵活性方面均受到限制.针对这些问题,融合5G网络和边缘计算技术,设计了基于5G多接入边缘计算的云化PLC系统架构,阐述了该架构的运行机制和所涉及的关键技术;在此基础上,进行PLC系统的云化部署和调试,实现了工业现场、企业数据中心、5G网络和边缘网络的集成;最后,通过在某汽车制造公司产线改造过程中的应用,验证了所提架构的有效性.

5G远程超声会诊模式在卫勤保障中的应用初探

本文对2021-05至2023-04武警上海总队医院的867例体检官兵,采用三种不同场景进行5G远程超声检查和会诊的实际应用效果进行评价。结果发现,5G远程超声会诊模式在三种应用场景的实际效果均较好,各自具有特点和需要改进的方面,适合在武警卫勤保障中的多场景应用。

考虑通信流量控制的配电网线路5G差动保护方案

针对5G通道承载配电网线路差动保护业务时数据流量大的问题,提出了考虑通信流量控制的配电网线路5G差动保护方案。从差动数据的发送频率、报文内容和报文类型入手,优化发送策略、简化数据格式、提高报文效率,并在此基础上优化差动保护数据同步方案和CT(电流互感器)饱和判别逻辑,大幅降低了数据流量,且不影响差动保护的性能,同时仍具备通道监视的功能。最后通过实验验证了该方案具备工程应用推广价值,为5G通信技术承载配电网差动保护业务的实用化提供了借鉴。

5G车联网中安全高效的组播服务认证与密钥协商方案

5G车联网(5G-V2X)中,内容提供者通过以点对多的传输方式向属于特定区域的一组车辆提供服务消息。针对于车辆获取组播服务遭受的安全威胁与隐私泄露问题,该文提出一种认证和密钥协商方案用于内容提供者与车辆之间的组播服务消息传输。首先,采用无证书聚合签名技术批量验证群组内所有车辆,提高了认证请求的效率。其次,基于多项式密钥管理技术实现安全的密钥协商,使得非法用户或核心网络无法获取共享会话密钥。最后,实现了群组内车辆的动态密钥更新机制,当车辆加入或离开群组时,内容提供者只需要发送1条密钥更新消息即可更新会话密钥。基于形式化验证工具和进一步安全性分析表明,所提方案可以保证匿名性、不可链接性、前向和后向安全性以及抗共谋攻击等安全需求。与现有方案相比,计算效率提高了约34.2%。

数字化技术在5G基站电磁辐射监测中的应用

介绍了一个基站电磁辐射数字化检测平台,该平台利用5G+互联网技术,实现了基站电磁辐射原始监测数据、频谱图的实时上传,以及基站电磁辐射监测的全要素、全流程管理,并结合CNAS实验室认可要求介绍了数字化检测系统投入应用时的注意事项。

配电网5G通信架构及其时延可靠性研究

5G在数字配电网领域的核心价值在于发挥5G的超高可靠、低时延技术优势,为配电网涉控业务提供高可靠、低时延的通信。为了系统地提供配电网5G通信时延与可靠性理论分析方案,结合数字配电网业务给出了配电网5G通信典型架构,深入分析了针对配电网5G通信的时延模型,针对国内四大运营商5G帧结构逐一进行了端到端时延分析,并通过5G链路级仿真了3GPP Rel-15和Rel-16的5G可靠性数值,提出了配电网5G通信的时延与可靠性联合分析方法。

民航领域5G加速推进背景下通信原理与系统课程教学改革

中国交通教育研究会“十四五”交通教育科研发展规划中明确指出,大力开展5G加速推进背景下专业课程教学创新方面的研究。中国民航大学通信原理与系统课程组立足民航发展需求,紧跟技术进步和行业发展的趋势,重组教学内容,深拓教学资源,探索多元化考核方式,开展“行业为要、内容为新”的课程教学改革,为民航5G加速推进背景下的课程建设提供参考和应用实践。

面向GPU的5G新型无线电的高吞吐率LDPC译码器

提出了一种基于图形处理单元(graphic processing unit,GPU)的5G软件无线电准循环低密度奇偶校验(low density parity check,LDPC)码译码器,为了节省片上和片下带宽,采用码字缩短和打孔技术、两级量化和数据打包方案,以提升数据带宽的利用率。实验基于Nvidia RTX 2080Ti GPU平台实现了高码率情况下的最小和近似译码算法的并行译码,通过分析GPU上的最优线程设置,将码率为5/6的(2080,1760)LDPC算法的译码吞吐率提升至1.38 Gbit/s,译码吞吐率性能优于现有其他基于GPU的LDPC译码器。